How to Use the Concord (Workflow Orchestration) MCP in Google ADK

Q: How do I restrict tool access for Concord (Workflow Orchestration) in Google ADK?

You can use the toolnames filter during setup. This limits your agent to only the functions you explicitly allow, keeping your configuration tight.

Connect your Google ADK agents to your deployment pipelines for automated workflow management.

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Connect Concord (Workflow Orchestration) MCP to Google ADK

Create your Vinkius account to connect Concord (Workflow Orchestration) to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Concord (Workflow Orchestration) with Google ADK

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Automate Pipelines in Google ADK

Trigger deployments or stop hung processes by calling `start_process` and `terminate_process`. Your agents now act on your infrastructure in real-time. Google ADK models use these tools to make decisions based on your current deployment status. It removes the need for manual intervention in your CI/CD flow.

Get Process Data via Google ADK

Fetch detailed execution history using `get_process` or see what is running right now with `list_running_processes`. It provides a clear snapshot of your cluster health. Your agent parses this information to decide whether to scale jobs or alert a human. It turns raw Concord data into actionable insights for your Google Cloud environment.

Organize Your Concord MCP Server

Navigate your organizations and repositories with `list_organizations` and `list_repositories`. Your agent builds a mental map of your entire setup. This makes it easy to find specific projects across a large instance. Google ADK agents use this structure to target the right repository for every task.

Setup guide

Set up Concord (Workflow Orchestration) MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Concord (Workflow Orchestration) tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Concord (Workflow Orchestration)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Concord (Workflow Orchestration) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Concord (Workflow Orchestration) MCP in Google ADK

You can use the tool_names filter during setup. This limits your agent to only the functions you explicitly allow, keeping your configuration tight.

Yes, the Gemini models in your framework handle long-context reasoning well. They track process status through `list_running_processes` over extended sessions without losing state.

You can feed your BigQuery results into the agent, which then uses those insights to trigger specific Concord processes. It links your data warehouse directly to your deployment actions.

Not at all. You just install the package and pass the server parameters to the McpToolset. It connects via standard HTTP or Stdio without extra overhead.

Your execution logs are fetched into the agent's memory for processing. All data transmissions are scoped to your secure endpoint and never stored on third-party servers.

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